Modern Computational Approaches to Traditional Chinese Medicine (Paperback)

Recognized as an essential component of Chinese culture, Traditional Chinese Medicine (TCM) is both an ancient medical system and one still used widely in China today. TCM's independently evolved knowledge system is expressed mainly in the Chinese language and the information is frequently only available through ancient classics and confidential family records, making it difficult to utilize. The major concern in TCM is how to consolidate and integrate the data, enabling efficient retrieval and discovery of novel knowledge from the dispersed data. Computational approaches such as data mining, semantic reasoning and computational intelligence have emerged as innovative approaches for the reservation and utilization of this knowledge system. Typically, this requires an inter-disciplinary approach involving Chinese culture, computer science, modern healthcare and life sciences. This book examines the computerization of TCM information and knowledge to provide intelligent resources and supporting evidences for clinical decision-making, drug discovery, and education. Recent research results from the Traditional Chinese Medicine Informatics Group of Zhejiang University are presented, gathering in one resource systematic approaches for massive data processing in TCM. These include the utilization of modern Semantic Web and data mining methods for more advanced data integration, data analysis and integrative knowledge discovery. This book will appeal to medical professionals, life sciences students, computer scientists, and those interested in integrative, complementary, and alternative medicine.

General

Imprint:	Elsevier - Health Sciences Division
Country of origin:	United States
Release date:	July 2012
First published:	2012
Editors:	Zhaohui Wu • Huajun Chen • Xiaohong Jiang
Dimensions:	229 x 152 x 13mm (L x W x T)
Format:	Paperback
Pages:	252
ISBN-13:	978-0-323-28272-7
Categories:	Books > Medicine > Other branches of medicine > Pharmacology > General
LSN:	0-323-28272-5
Barcode:	9780323282727

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